search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
MAINTENANCE FEATURE BASIC, BETTER, BEST – THE TOOLS OF THE TRADE


As the power and flexibility of digital maintenance systems evolves, it is important to pick the right tool for each job. SKF explains the benefits of a tiered basic, better, best approach


C


ondition-based and predictive maintenance might be Industry 4.0’s


“killer app”. In sectors from manufacturing to energy, companies are exploring the application of digitally-enabled approaches to monitor asset health and performance. The methods vary, but the goals are always the same: reducing maintenance costs and minimising both planned and unplanned downtime. Operations and maintenance staff have


increasingly sophisticated techniques at their disposal, including systems that use artificial intelligence and machine learning to spot the signs of problems in complex asset data. In a survey of German engineering companies conducted by consultancy Roland Berger, 81 per cent said they were currently devoting time and resources to the topic of predictive maintenance. The market for maintenance technologies and services is growing at more than 25 percent a year and could be worth $11 billion worldwide by 2022. The proliferation of digital monitoring


and analysis technologies brings its own challenges, however. Most companies operate a range of mechanical assets, from complex production machines to simple pumps and fans. Each of these assets may be at risk of different potential issues, which may have many different consequences; these can range from a small reduction in performance or efficiency to catastrophic failure. With such a wide range of possible issues


and outcomes, companies often struggle to allocate resources effectively. Where should they invest in digital monitoring and maintenance approaches? Which technologies deliver the fastest payback? SKF has been involved in the analysis


and optimisation of rotating equipment performance for decades and has found that many organisations find it beneficial


to take a pragmatic, tiered approach to their condition-based maintenance strategy: assigning assets to one of three broad categories, and allocating time, resources and technology accordingly. This is the “basic, better, best” approach. Basic asset care –The simplest


monitoring tools include portable, handheld devices or permanently installed sensors capable of measuring changes in vibration or operating temperatures in both mechanical and electrical systems. In-house maintenance technicians can use hand-held devices for routine walk- through machine data collection.


Using wireless connectivity, data collected by operators can be immediately available for further analysis, either by in- house maintenance personnel or, via the Cloud by third party specialists. This approach effectively puts deep condition monitoring expertise into the hands of every operator


Allowing customers to choose the level that best suits their needs ensures that they will be able to operate assets more dependably, affordably, productively and profitably


Where continuous vibration and


temperature monitoring of non-critical machinery is desired, permanently installed condition indicators are available. These inexpensive sensors can measure a range of parameters, including velocity, enveloped acceleration (bearing or gear impulsive vibration) and machine surface temperature. Equipped with LEDs that illuminate when pre-set thresholds have been exceeded; they act as a warning that further investigation is needed. Better asset care –The next level of


sophistication in condition-based maintenance involves an increase in the quantity of data collected, either through greater frequency of measurement or a wider range of parameters. It does not necessarily require additional equipment. Operator Driven Reliability (ODR)


programmes, for example, take advantage of the fact that operators work in close proximity to equipment, so they are usually the first to detect changes in process conditions and machinery health. Equipping operators with their own hand- held data collection devices and appropriate software empowers them to become active participants in condition- based maintenance, taking routine measurements and conducting early investigations when issues arise. Using wireless connectivity, data


collected by operators can be immediately available for further analysis, either by in- house maintenance personnel or, via the Cloud by third party specialists. Not every application lends itself to the


Modern hand-held units include wireless


communication, allowing them to transmit measurements seamlessly to a central repository. That saves technicians time and allows the full or partial automation of analytical tasks, such as tracking trends.


use of hand-held data collection devices. Some machines may operate unattended, for example, or access may be difficult for safety reasons. Here companies can use permanently installed health monitoring systems, which collect data from multiple fixed sensors. These systems suit a range of applications, from a full manufacturing plant to a single machine. Best asset care –For the most critical


Modern hand-held data collection units include wireless communication capabilities, allowing them to transmit measurements seamlessly to a central repository





assets, companies can move to a fully on- line condition monitoring approach. Networked sensors and machine control systems can send their data to Cloud- based analytics and storage platforms. Once there, analytical tools and human expertise are applied to identify issues, predict problems and advise on appropriate maintenance interventions. Allowing customers to choose the level


that best suits their needs ensures that they will be able to operate assets more dependably, affordably, productively and profitably, for many years to come.


SKF (UK) www.skf.co.uk


PROCESS & CONTROL | JULY/AUGUST 2019 45


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60